Abstract: The nanoscale morphology of polymer blends is a key parameter to reach high efficiency in bulk heterojunction solar cells. Thereby, research typically focusing on optimal blend morphologies while studying nonoptimized blends may give insight into blend designs that can prove more robust against morphology defects. Here, we focus on the direct correlation of morphology and device performance of thieno[3,4-b]-thiophene-alt-benzodithiophene (PTB7):[6,6]phenyl C-71 butyric acid methyl ester (PC71BM) bulk heterojunction (BHJ) blends processed without additives in different donor/acceptor weight ratios. We show that while blends of a 1:1.5 ratio are composed of large donor-enriched and fullerene domains beyond the exciton diffusion length, reducing the ratio below 1:0.5 leads to blends composed purely of polymer-enriched domains. Importantly, the photocurrent density in such blends can reach values between 45 and 60% of those reached for fully optimized blends using additives. We provide here direct visual evidence that fullerenes in the donor-enriched domains are not distributed homogeneously but fluctuate locally. To this end, we performed compositional nanoscale morphology analysis of the blend using spectroscopic imaging of low-energy-loss electrons using a transmission electron microscope. Charge transport measurement in combination with molecular dynamics simulations shows that the fullerene substructures inside the polymer phase generate efficient electron transport in the polymer-enriched phase. Furthermore, we show that the formation of densely packed regions of fullerene inside the polymer phase is driven by the PTB7:PC71BM enthalpy of mixing. The occurrence of such a nanoscale network of fullerene clusters leads to a reduction of electron trap states and thus efficient extraction of photocurrent inside the polymer domain. Suitable tuning of the polymer-acceptor interaction can thus introduce acceptor subnetworks in polymer-enriched phases, improving the tolerance for high-efficiency BHJ toward morphological defects such as donor-enriched domains exceeding the exciton diffusion length.

Abstract: The original motivation to study Generalized Möbius-Listing GML surfaces and bodies was the observation that the solution of boundary value problems greatly depends on the domains. Since around 2010 GML’s were merged with (continuous) Gielis Transformations, which provide a unifying description of geometrical shapes, as a generalization of the Pythagorean Theorem. The resulting geometrical objects can be used for modeling a wide range of natural shapes and phenomena. The cutting of GML bodies and surfaces, with the Möbius strip as one special case, is related to the field of knots and links, and classifications were obtained for GML with cross sectional symmetry of 2, 3, 4, 5 and 6. The general case of cutting GML bodies and surfaces, in particular the number of ways of cutting, could be solved by reducing the 3D problem to planar geometry. This also unveiled a range of connections with topology, combinatorics, elasticity theory and theoretical physics.

Abstract: This dataset comprises a large collection of atom probe tomography datasets collected from DIN 1.4970 alloy that was irradiated with Fe ions at different conditions. The DIN 1.4970 alloy is an austenitic stainless steel with 15 wt% Cr, 15 wt% Ni, a small addition of Ti. The full composition and characterization of our material can be found published elsewhere [1,2]. Some of our material was subjected to ageing heat treatments at different temperatures for different times. Small samples of our original material and aged material was irradiated at the Michigan Ion Beam Laboratory in 2017 with 4.5 MeV Fe ions up to 40 dpa at an average dose rate of 2×10−4 dpa/s. This was done at three different temperatures: 300, 450, and 600 ºC. Atom probe samples were made of the irradiated layers (approximately 1.5 micron deep) with focused ion beam and mounted on Microtip coupons. APT measurements took place on three CAMECA LEAP-HR systems located at CAES in Idaho Falls, USA (files beginning with R33), at Montanuniversität Leoben in Leoben, Austria (R21) and at Friedrich–Alexander University in Erlangen, Germany (R56).

Abstract: Biobased chemistry has gained interest and has the potential to tackle some of the sustainability challenges the chemical industry must endure. Sustainability impacts need to be evaluated and monitored to highlight the advantages and pitfalls of different biobased routes over the product life cycle. A better understanding of the potential sustainability of emerging biobased technologies and products is essential to guide additional research and further technology development. This PhD thesis aims to develop a framework for a techno-sustainability assessment (TSA), while accounting for technological as well as economic, environmental, and social aspects in an integrated approach. First, a review of the state-of-the-art sustainability indicators for biobased chemicals was conducted and a gap analysis was performed to identify indicator development needs. Afterwards, a Delphi study was performed to select sustainability indicators specifically for biobased chemical assessment and to reach consensus among experts on a prioritization of these indicators. Next, the selected sustainability indicators were quantified while integrating technological and country-specific data with environmental characterization factors, economic values and social data. Finally, a stochastic, hierarchical multi-criteria decision analysis (MCDA) integrates the independent techno-sustainability indicators expressed in different units, taking into account stochastic and flexible method options. The developed integrated TSA framework was applied to a case for which a production and harvesting plant of microalgae-based food colorants is assessed. The final aim of the integrated TSA is to compare the potential sustainability performance of different scenarios and to make better-informed choices between alternatives by evaluating environmental, economic and social sustainability impacts in one holistic model. Integrated TSA offers a novel framework where decision makers can assess sustainability already in early technology development stages by identifying potential hurdles and opportunities to guide R&D and make sustainable investment decisions.